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The end of
the scientific paper
as we know it
(in 4 easy steps)
Frank van Harmelen
Paul Groth
VU Amsterdam
And how the Semantic Web
makes it possible
Scientific publishing hasn’t changed
in 350 years
• Letter from Christian Huygens (1652)
• Writing to his prof in Mathematics
• Citing (and complaining about)
work of Descartes
• One of 3000 letters by Huygens
2017: Only superficial changes
• Different format & style
• Different medium
(Web, PDF)
• Different speed
(PubMed = 2 papers/min)
Section 1: Related work
Section 2: Research question
Section 3: Experimental design
Section 4: Experimental findings
Section 5: Interpretation, conclusions
And our papers still follow
this storyline:
Step 1: Study & interpret literature
Step 2: Formulate hypothesis
Step 3: Design experiment
Step 4: Execute experiment
Step 5: Publish results
This storyline is important,
but only readable by people,
not for machines
How to make our papers more usable?
“We only need information extraction
because we first did information burial” (Barend Mons)
“A journal paper
is a state-funeral
for your results”
(Hans Akkermans)
Step 1: explicit rhetorical structure
Capture the roles of blocks of text &
make these roles explicit
1 paper = 1 Network of blocks
N papers = 1 Network of blocks
Results Results
Interpretati
ons
Interpretati
ons
Conclusio
ns
Problem
Method
Results
Interpretati
ons
Conclusio
ns
Problem
Method
One paper Another paper
Step 2: explicit fine-grained
rhetorical structure
Locate individual knowledge items
and their relationships
Example: Scholonto, ClaiMaker [Buckinham-Shum]
Paper = set of claims
Claim = text – relation – text
Relation = causes, predicts, prevents; addresses, solves
equals, is-similar-to; proofs, supports, challenges
1 paper = 1 fine-grained network of relations
N papers = 1 fine-grained network of relations
Step 3: do away with the paper altogether.
• Any fact is a relation between two things (“triple”)
• Count each fact as a nano-publication
• Together, these nano-publications form a
huge very fine-grained network of relations,
a web of knowledge,
a “semantic web”
• Computers as colleagues,
not (only) tools
Just publish the facts
Step 4: turning context into a
1st class citizen
• Link to all the stuff that goes on before publication:
– Datasets, workflows
– Open Lab books
– Open peer reviewing
• Link to all the stuff that goes on after publication:
– Websites
– Blogs
– Emails
– Tweets
– Give web-addresses to objects (URIs)
– Use the web to link between the objects
– Provide meaning in a form that computers can handle (RDF)
These principles embodied
in already deployed technology
We can build this using
semantic web technology
So now we have…
No longer a set of
disconnected monolithic PDFs
A network of facts, reviews,
evidence, opinions, data

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The end of the scientific paper as we know it (in 4 easy steps)

  • 1. The end of the scientific paper as we know it (in 4 easy steps) Frank van Harmelen Paul Groth VU Amsterdam And how the Semantic Web makes it possible
  • 2. Scientific publishing hasn’t changed in 350 years • Letter from Christian Huygens (1652) • Writing to his prof in Mathematics • Citing (and complaining about) work of Descartes • One of 3000 letters by Huygens
  • 3. 2017: Only superficial changes • Different format & style • Different medium (Web, PDF) • Different speed (PubMed = 2 papers/min)
  • 4. Section 1: Related work Section 2: Research question Section 3: Experimental design Section 4: Experimental findings Section 5: Interpretation, conclusions And our papers still follow this storyline: Step 1: Study & interpret literature Step 2: Formulate hypothesis Step 3: Design experiment Step 4: Execute experiment Step 5: Publish results This storyline is important, but only readable by people, not for machines
  • 5. How to make our papers more usable? “We only need information extraction because we first did information burial” (Barend Mons) “A journal paper is a state-funeral for your results” (Hans Akkermans)
  • 6. Step 1: explicit rhetorical structure Capture the roles of blocks of text & make these roles explicit 1 paper = 1 Network of blocks N papers = 1 Network of blocks Results Results Interpretati ons Interpretati ons Conclusio ns Problem Method Results Interpretati ons Conclusio ns Problem Method One paper Another paper
  • 7. Step 2: explicit fine-grained rhetorical structure Locate individual knowledge items and their relationships Example: Scholonto, ClaiMaker [Buckinham-Shum] Paper = set of claims Claim = text – relation – text Relation = causes, predicts, prevents; addresses, solves equals, is-similar-to; proofs, supports, challenges 1 paper = 1 fine-grained network of relations N papers = 1 fine-grained network of relations
  • 8.
  • 9. Step 3: do away with the paper altogether. • Any fact is a relation between two things (“triple”) • Count each fact as a nano-publication • Together, these nano-publications form a huge very fine-grained network of relations, a web of knowledge, a “semantic web” • Computers as colleagues, not (only) tools Just publish the facts
  • 10.
  • 11. Step 4: turning context into a 1st class citizen • Link to all the stuff that goes on before publication: – Datasets, workflows – Open Lab books – Open peer reviewing • Link to all the stuff that goes on after publication: – Websites – Blogs – Emails – Tweets
  • 12. – Give web-addresses to objects (URIs) – Use the web to link between the objects – Provide meaning in a form that computers can handle (RDF) These principles embodied in already deployed technology We can build this using semantic web technology
  • 13. So now we have… No longer a set of disconnected monolithic PDFs A network of facts, reviews, evidence, opinions, data

Editor's Notes

  1. Use circular diagram?